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Correspondence| Volume 16, ISSUE 6, P533-535, November 2022

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Head to head comparison reproducibility and inter-reader agreement of an AI based coronary stenosis algorithm vs level 3 readers

Published:May 04, 2022DOI:https://doi.org/10.1016/j.jcct.2022.04.005
Head to head comparison reproducibility and inter-reader agreement of an AI based coronary stenosis algorithm vs level 3 readers
Previous ArticleLong term prognostic value for a normal CCTA
Next ArticleCAD-RADS™ 2.0 - 2022 Coronary Artery Disease-Reporting and Data System
      The reproducibility of coronary stenosis grading in clinical practice using coronary CT angiography (CCTA) has been modest particularly amongst less experienced readers.
      • Maroules C.D.
      • Hamilton-Craig C.
      • Branch K.
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      Coronary artery disease reporting and data system (CAD-RADS(TM)): inter-observer agreement for assessment categories and modifiers.
      J Cardiovasc Comput Tomogr. Mar - Apr 2018; 12: 125-130https://doi.org/10.1016/j.jcct.2017.11.014
      ,
      • Williams M.C.
      • Golay S.K.
      • Hunter A.
      • et al.
      Observer variability in the assessment of CT coronary angiography and coronary artery calcium score: substudy of the Scottish COmputed Tomography of the HEART (SCOT-HEART) trial.
      Open Heart. 2015; 2e000234https://doi.org/10.1136/openhrt-2014-000234
      With the advancement of artificial intelligence (AI) based coronary segmentation, there are opportunities to support improvements in the reproducibility of stenosis assessment.
      • Nakanishi R.
      • Motoyama S.
      • Leipsic J.
      • Budoff M.J.
      How accurate is atherosclerosis imaging by coronary computed tomography angiography?.
      J Cardiovasc Comput Tomogr. Sep - Oct 2019; 13: 254-260https://doi.org/10.1016/j.jcct.2019.06.005
      In this study, we assessed the performance an AI-based algorithm with analyst input in evaluation of coronary luminal stenosis by comparing its agreement and reproducibility to those of experienced CCTA readers.
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      References

        • Maroules C.D.
        • Hamilton-Craig C.
        • Branch K.
        • et al.
        Coronary artery disease reporting and data system (CAD-RADS(TM)): inter-observer agreement for assessment categories and modifiers.
        J Cardiovasc Comput Tomogr. Mar - Apr 2018; 12: 125-130https://doi.org/10.1016/j.jcct.2017.11.014
        View in Article
        • Williams M.C.
        • Golay S.K.
        • Hunter A.
        • et al.
        Observer variability in the assessment of CT coronary angiography and coronary artery calcium score: substudy of the Scottish COmputed Tomography of the HEART (SCOT-HEART) trial.
        Open Heart. 2015; 2e000234https://doi.org/10.1136/openhrt-2014-000234
        View in Article
        • Nakanishi R.
        • Motoyama S.
        • Leipsic J.
        • Budoff M.J.
        How accurate is atherosclerosis imaging by coronary computed tomography angiography?.
        J Cardiovasc Comput Tomogr. Sep - Oct 2019; 13: 254-260https://doi.org/10.1016/j.jcct.2019.06.005
        View in Article
        • Taylor C.A.
        • Fonte T.A.
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        Computational fluid dynamics applied to cardiac computed tomography for noninvasive quantification of fractional flow reserve: scientific basis.
        J Am Coll Cardiol. Jun 4 2013; 61: 2233-2241https://doi.org/10.1016/j.jacc.2012.11.083
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        CAD-RADS(TM) coronary artery disease - reporting and data system. An expert consensus document of the Society of Cardiovascular Computed Tomography (SCCT), the American College of Radiology (ACR) and the North American Society for Cardiovascular imaging (NASCI). Endorsed by the American College of Cardiology.
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        View in Article

      Article info

      Publication history

      Published online: May 04, 2022
      Accepted: April 29, 2022
      Received in revised form: April 5, 2022
      Received: February 15, 2022

      Identification

      DOI: https://doi.org/10.1016/j.jcct.2022.04.005

      Copyright

      © 2022 Society of Cardiovascular Computed Tomography. Published by Elsevier Inc. All rights reserved.

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